Watt’s Powering the Data Center
AI is reshaping global electricity demand, with data centers quickly becoming major power consumers. How much power do they draw today, and where might that demand be headed in the years ahead?
The rise of artificial intelligence (AI) is reshaping global electricity demand as data centers grow into some of the largest power consumers on the grid. Power is measured in watts, with the average U.S. home pulling roughly 1,000 watts. A thousand homes add up to roughly a megawatt, and a million homes to a gigawatt (GW). Where could data center power consumption be headed over the next several years?
- In the chart above, global AI data center power capacity has had a ~78x increase in under four years. Currently, the global AI data center footprint already draws more power than the peak demand of New York State. Looking ahead, we estimate that global data center power capacity could surpass the peak power draw of Japan by the end of 2028. Inside a typical AI data center, the largest power draws come from compute servers and cooling systems, followed by power delivery equipment, networking gear, and storage arrays.
- Hyperscalers are now building data center campuses that exceed 1 GW of power capacity, equivalent to powering 750,000 to 1 million U.S. homes or the average power draw of a city the size of Nashville, Tennessee. In the U.S., power demand of this magnitude is outpacing what the grid can deliver, with grid connection wait times stretching five to seven years in many regions. To avoid those delays, hyperscalers are increasingly turning to onsite power generation, deploying technologies such as gas turbines, reciprocating engines, and fuel cells directly at their data center campuses (see also The AI Power Problem).
- We believe the magnitude of this buildout has meaningful investment implications across the power infrastructure space, including utilities, independent power producers, electrical equipment manufacturers, and grid technology providers. In our view, meeting AI's power needs will likely require sustained capital investment well beyond the data center itself, creating potential opportunities in companies positioned to supply the generation, transmission, and distribution capacity that the next phase of AI growth depends on.
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